Comprehensive Analysis and Research on the Mainstream Algorithm of Machine Learning in Stock Trend Prediction

The rapid growth of the equity market has progressively become an essential pillar of the nation's economy. The stock market can generate high returns. our research focuses on how to accurately foresee the stock price trend. In this paper, Fenghua high-tech stock data is chosen as the experimental data, and stock movements are predicted using the support vector machine (SVM) model, the LGBM model, and the random forests (FM) model. On the premise of empirical research, the prediction effect and accuracy of each model are demonstrated by integrating the prediction curve of each model with the evaluation indices RMSE, MAE, MAPE, and R2. The results indicate that the model based on random forest provides more accurate predictions.